Grain number (GN) is determined by spike growth rate (SGR), fruiting efficiency (FE) and the duration of spike growth period (Ds). However, these three traits are not independent of each other and therefore quantifying their relative contribution to GN is important for improving yield potential. This study aimed to model GN as a function of SGR, FE and Ds in bread wheat and investigate the relative importance of these three traits in determining GN. A large number of commercial varieties, elite wheat breeding lines, and a Multiparent Advanced Generation InterCross population were evaluated for GN, SGR, Ds, and FE in six Australian environments in 2014 and 2015. The model explained 43–98% of the variation in GN in individual environments and 88% of the variation in GN across the six environments. The percentage of GN variance explained by the model was significantly higher than those explained by correlating GN to individual traits. The relative importance of the contribution of the three traits to GN was different and ranked as SGR > FE > Ds. The negative correlation between FE and spike dry weight at anthesis (SDWa) appears to be spurious, suggesting that there was no causality between high FE and low SDWa and vice versa. Thus, FE can be used as an independent trait to increase GN in addition to SGR and Ds. We also investigated if the wheat crop had enough source to fill the increased sink size in the southern Australian high rainfall environment. The source-sink balance analysis indicates that the available source, consisting of concurrent photosynthetic assimilate and stored water-soluble carbohydrate at anthesis, was sufficient to fill the established sink but no surplus assimilates were available to fill a larger sink in southwestern Australia. However, the opportunity to increase yield potential by further increasing grain number might exist in south-eastern Australia environments.

中文翻译：

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小麦粒数和产量：澳大利亚南部生理性状和源库平衡的相对重要性

籽粒数 (GN) 由穗生长率 (SGR)、结果效率 (FE) 和穗生长期持续时间 (Ds) 决定。然而，这三个性状并不是相互独立的，因此量化它们对 GN 的相对贡献对于提高产量潜力很重要。本研究旨在将 GN 建模为面包小麦中 SGR、FE 和 Ds 的函数，并研究这三个性状在确定 GN 中的相对重要性。2014 年和 2015 年在澳大利亚的六个环境中评估了大量商业品种、优良小麦育种品系和多亲先进一代 InterCross 种群的 GN、SGR、Ds 和 FE。该模型解释了 43-98% 的变异单个环境中的 GN 和六个环境中 88% 的 GN 变化。模型解释的 GN 方差百分比显着高于通过将 GN 与个体特征相关联解释的百分比。三个性状对 GN 贡献的相对重要性不同，排序为 SGR > FE > Ds。FE 与花期穗干重 (SDWa) 之间的负相关似乎是虚假的，这表明高 FE 和低 SDWa 之间没有因果关系，反之亦然。因此，除了 SGR 和 Ds 之外，FE 还可以用作增加 GN 的独立特征。我们还调查了小麦作物是否有足够的来源来填补澳大利亚南部高降雨量环境中增加的汇。源库平衡分析表明，可用的来源，包括并发的光合同化物和开花时储存的水溶性碳水化合物，足以填充已建立的水槽，但没有多余的同化物可用于填充澳大利亚西南部的更大水槽。然而，在澳大利亚东南部的环境中可能存在通过进一步增加谷物数量来提高产量潜力的机会。